This volume collects selected papers from the 7th High Dimensional Probability meeting held at the Institut d'Etudes Scientifiques de Cargese (IESC) in Corsica, France.
Focusing on stochastic porous media equations, this book places an emphasis on existence theorems, asymptotic behavior and ergodic properties of the associated transition semigroup.
The contributions by epidemic modeling experts describe how mathematical models and statistical forecasting are created to capture the most important aspects of an emerging epidemic.
This book employs a computable general equilibrium (CGE) model - a widely used economic model which uses actual data to provide economic analysis and policy assessment - and applies it to economic data on Singapore's tourism industry.
This book offers a detailed analysis of the key sectors in the Italian economy, with the focus especially on areas in which the economy excels, such as the automatic packaging machinery sector, pharmaceutical production, the food and wine industry, and tourism.
This unique text presents a comprehensive review of methods for modeling signal and noise in magnetic resonance imaging (MRI), providing a systematic study, classifying and comparing the numerous and varied estimation and filtering techniques.
This brief broadens readers' understanding of stochastic control by highlighting recent advances in the design of optimal control for Markov jump linear systems (MJLS).
This monograph deals with the mathematics of extending given partial data-sets obtained from experiments; Experimentalists frequently gather spectral data when the observed data is limited, e.
This book presents a philosophical approach to probability and probabilistic thinking, considering the underpinnings of probabilistic reasoning and modeling, which effectively underlie everything in data science.
This book has developed over the past fifteen years from a modern course on stochastic chemical kinetics for graduate students in physics, chemistry and biology.
This book is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical biological and life science problems.
This book constitutes the thoroughly refereed proceedings of the 23rd International Conference on Computer Networks, CN 2016, held in Brunow, Poland, in June 2016.
This introductory textbook for business statistics teaches statistical analysis and research methods via business case studies and financial data using Excel, Minitab, and SAS.
This is a self-contained exposition by one of the leading experts in lattice theory, George Gratzer, presenting the major results of the last 70 years on congruence lattices of finite lattices, featuring the author's signature Proof-by-Picture method.
This brief is a clear, concise description of the main techniques of time series analysis -stationary, autocorrelation, mutual information, fractal and multifractal analysis, chaos analysis, etc.
The research articles in this volume cover timely quantitative psychology topics, including new methods in item response theory, computerized adaptive testing, cognitive diagnostic modeling, and psychological scaling.
Presenting the latest findings in topics from across the mathematical spectrum, this volume includes results in pure mathematics along with a range of new advances and novel applications to other fields such as probability, statistics, biology, and computer science.
This volume presents the lecture notes from two courses given by Davar Khoshnevisan and Rene Schilling, respectively, at the second Barcelona Summer School on Stochastic Analysis.
This book presents 8 tutorial lectures given by leading researchers at the 16th edition of the International School on Formal Methods for the Design of Computer, Communication and Software Systems, SFM 2016, held in Bertinoro, Italy, in June 2016.
This book presents a wide range of well-known and less common methods used for estimating the accuracy of probabilistic approximations, including the Esseen type inversion formulas, the Stein method as well as the methods of convolutions and triangle function.
This book takes a unique approach to explaining permutation statistics by integrating permutation statistical methods with a wide range of classical statistical methods and associated R programs.
This monograph aims to promote original mathematical methods to determine the invariant measure of two-dimensional random walks in domains with boundaries.
Presenting a novel biomimetic design method for transferring design solutions from nature to technology, this book focuses on structure-function patterns in nature and advanced modeling tools derived from TRIZ, the theory of inventive problem-solving.
This book presents methods for investigating whether relationships are linear or nonlinear and for adaptively fitting appropriate models when they are nonlinear.
This volume presents a unified mathematical framework for the transmission channels for damaging shocks that can lead to instability in financial systems.
Marking the 30th anniversary of the European Conference on Modelling and Simulation (ECMS), this inspirational text/reference reviews significant advances in the field of modelling and simulation, as well as key applications of simulation in other disciplines.
This is a comprehensive survey on the research on the parabolic Anderson model - the heat equation with random potential or the random walk in random potential - of the years 1990 - 2015.
This book elaborates on the asymptotic behaviour, when N is large, of certain N-dimensional integrals which typically occur in random matrices, or in 1+1 dimensional quantum integrable models solvable by the quantum separation of variables.
Presenting an analysis of different approaches for predicting the service life of buildings, this monograph discusses various statistical tools and mathematical models, some of which have rarely been applied to the field.
This book traces the theory and methodology of multivariate statistical analysis and shows how it can be conducted in practice using the LISREL computer program.
This book presents a systematic and comprehensive treatment of various prior processes that have been developed over the past four decades for dealing with Bayesian approach to solving selected nonparametric inference problems.
Taking the Lasso method as its starting point, this book describes the main ingredients needed to study general loss functions and sparsity-inducing regularizers.
This textbook teaches advanced undergraduate and first-year graduate students in Engineering and Applied Sciences to gather and analyze empirical observations (data) in order to aid in making design decisions.
